【正文】 附錄外文資料原文The simulation and the realization of the digital filterLv Tiejun,Guo Shuangbing,Xiao XianciThe first chapter figures UnitonIn signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the ponents lying within a certain frequency range. There are two main kinds of filter, analog and digital. They are quite different in their physical makeup and in how they work. An analog filter uses analog electronic circuits made up from ponents such as resistors, capacitors and opamps to produce the required filtering effect. Such filter circuits are widely used in such applications as noise reduction, video signal enhancement, graphic equalisers in hifi systems, and many other areas. There are wellestablished standard techniques for designing an analog filter circuit for a given requirement. At all stages, the signal being filtered is an electrical voltage or current which is the direct analogue of the physical quantity (. a sound or video signal or transducer output) involved. A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a generalpurpose puter such as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitised using an ADC (analog to digital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to the processor, which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.Unit refers to the input signals used to filter hardware or software. If the filter input, output signals are separated, they are bound to respond to the impact of the Unit is separated, such as digital filters filter definition. Digital filter function, which was to import sequences X transformation into export operations through a series Y.According to figures filter function 24hour live response characteristics, digital filters can be divided into two, namely, unlimited long live long live the corresponding IIR filter and the limited response to FIR filters. IIR filters have the advantage of the digital filter design can use simulation results, and simulation filter design of a。誤差逼近39。)。ylabel(39。頻率/(w/pi) 39。)。title(39。幅度增益/dB)39。)。figure plot(W/pi,20*log10(abs(H)))axis([0,1,100,10])xlabel(39。幅度響應(yīng)圖39。)。ylabel(39。頻率/(w/pi) 39。 subplot(2,1,2)plot(W/pi,A)。沖激響應(yīng)39。)。ylabel(39。n 39。MarkerSize39。fill39。A=cos(W1*k)*a39。W1=[0:1:511]39。a=[h(L+1),2*h(L:1:1)]。L=M/2。 [h,err,res]=firpm(M,F,Ad,W)。K=deltap/deltas。F=[0,wp,ws,pi]/pi。 wm=wswp。deltap=。freqz(b)附錄五：最優(yōu)等波紋線性相位FIR低通濾波器wp=*pi。a=[0,0,1]。附錄四：頻率采樣濾波器設(shè)計(jì)的高通濾波器n=50。信號濾波后頻域圖39。)。ylabel(39。頻率/赫茲39。 %濾波后的信號頻域圖及信號頻域圖的幅值f=(0:255)*fs/512。 %限定圖像坐標(biāo)范圍subplot(212)Fsf=fft(sf,512)。)。title(39。幅度39。)。 %使用filter函數(shù)對信號進(jìn)行濾波subplot(211)plot(t,sf) %濾波后的信號圖像xlabel(39。)。title(39。幅度39。)。 %濾波前的信號頻域圖xlabel(39。 %將信號變換到頻域及信號頻域圖的幅值f=(0:255)*fs/512。subplot(212)Fs=fft(s,512)。信號濾波前時(shí)域圖39。)。ylabel(39。時(shí)間/秒39。 %濾波前信號plot(t,s)。t=0:1/fs:。axis([0 1 50 ])。濾波器的增益響應(yīng)39。)。ylabel(39。歸一化角頻率39。 %濾波器的幅頻特性圖figure(1)plot(w/pi,20*log10(abs(H)))。%h（n）=IDFT[H(k)]w=linspace(0,pi,1000)。 %構(gòu)造頻域采樣向量H(k)Hd=[Hd conj(fliplr(Hd(2:(M+1)/2)))]。AD(mr)=。 %向負(fù)方向入floor()=3。 Wm=2*pi*m./(M1)。 Wp=*pi。)。title(39。幅度39。)。 %頻率采樣plot(f,AFsf(1:256)) %濾波后的信號頻域圖xlabel(39。 %濾波后的信號頻域圖AFsf=abs(Fsf)。)。title(39。幅度39。)。 %對信號s進(jìn)行濾波；subplot(211)plot(t,sf)%濾波后的信號圖像；xlabel(39。)。title(39。幅度39。)。 %濾波前的信號頻域圖xlabel(39。 %信號頻域圖的幅值f=(0:255)*fs/512。subplot(212)Fs=fft(s,512)。信號濾波前時(shí)域圖39。)。ylabel(39。時(shí)間/秒39。plot(t,s)。s=sin(2*pi*200*t)+sin(2*pi*500*t)+sin(2*pi*800*t)+sin(2*pi*750*t)。)。title(39。增益/分貝39。)。plot(f*fs/(2*pi),20*log10(abs(h)))xlabel(39。b=fir1(m,wc,ftype,kaiser(m+1,beta))。fs2=750。fp2=650。附錄二：利用Hamming窗設(shè)計(jì)帶通濾波器的程序fs=2000。信號濾波后頻域圖39。)。ylabel(39。頻率/赫茲39。 %信號頻域圖的幅值f=(0:255)*fs/512。subplot(212)Fsf=fft(sf,512)。信號濾波前時(shí)域圖39。)。ylabel(39。時(shí)間/秒39。figure(3)sf=filter(b,1,s)。信號濾波前頻域圖39。)。ylabel(39。頻率/赫茲39。 %頻率采樣plot(f,AFs(1:256))。 %將信號變換到頻域AFs=abs(Fs)。)。title(39。幅度39。)。 %濾波前的信號圖像； xlabel(39。 %混和正弦波信號。figure(2)subplot(211)t=(1:100)/fs。濾波器的增益響應(yīng)39。)。ylabel(39。頻率/赫茲39。 %使用標(biāo)準(zhǔn)頻率響應(yīng)的加窗設(shè)計(jì)函數(shù)fir1；figure(1)[h,f]=freqz(b,1,512)。 %得出濾波器的階數(shù)w=2*fc/fs %模擬到數(shù)字濾波器的技術(shù)指標(biāo)的轉(zhuǎn)換window=kaiser(n+1,beta)。fs=10000。無論我成功與否，你們總以鼓勵(lì)的言語告訴我很棒，謝謝你們，我會(huì)繼續(xù)努力。最后要感謝的是我的父母和家人，我永遠(yuǎn)都不會(huì)忘記你們的良苦用心和一如既往的支持與鼓勵(lì)。生活中，他教我如何真誠做人，坦誠做事，每次談話都如同春風(fēng)化雨，在設(shè)計(jì)論文的每一個(gè)過程里都凝聚了的心血，在此謹(jǐn)向老師表示最真摯的謝意和崇高的敬意。他嚴(yán)肅的科學(xué)態(tài)度，嚴(yán)謹(jǐn)?shù)闹螌W(xué)精神，精益求精的工作作風(fēng)，深深的感染和激勵(lì)著我。2002, [2][J]. 遼寧工程技術(shù)大學(xué)學(xué)報(bào), 2005, : 716718[3]丁吉，[J].長春工業(yè)大學(xué)學(xué)報(bào),20060726 [4] 閆勝利. FIR濾波器及設(shè)計(jì)原理[J]. 長春工程學(xué)院學(xué)報(bào)(自然科學(xué)版), 200364[5]楊永昌,李晨輝,王凱. FIR數(shù)字濾波器的設(shè)計(jì)方法[J]. 桂林航天工業(yè)高等專科院校學(xué)報(bào), 2006115[6] and . Manolakis, Digital Signal ProcessingPrinciples,Algorithms and Applications New Delhi: PrenticeHall, 2000[7],The Mathworks,Inc., accessed October 25,2002?？傊?，這次畢業(yè)設(shè)計(jì)對我而言是受益匪淺的。整體而言，通過本次畢業(yè)設(shè)計(jì)，我感到自己應(yīng)用基礎(chǔ)知識及專業(yè)知識解決問題的能力有了很大的提高，在我即將進(jìn)入下一階段的工作學(xué)習(xí)之前，它是一次重要演練。b) 進(jìn)一步學(xué)習(xí)matlab軟件，熟練掌握matlab在數(shù)字信號處理中的運(yùn)用。 對今后工作學(xué)習(xí)的展望設(shè)計(jì)出與設(shè)計(jì)指標(biāo)最逼近的FIR數(shù)字濾波器，需要對三種濾波器有較深的理解和非常熟練的運(yùn)用matlab軟件的能力。但是本文中僅僅考慮了一種或者兩種，這樣設(shè)計(jì)出的濾波器誤差較大。 本文存在的問題本文雖然對三種濾波器進(jìn)行了詳細(xì)的設(shè)計(jì)分析，并可以通過他們對不同信號進(jìn)行濾波，但是在制定三種濾波器的設(shè)計(jì)參數(shù)時(shí)，過于簡單粗糙。窗函數(shù)法和頻率采樣法設(shè)計(jì)濾波器時(shí)濾波器的邊界頻率不易精確控制，通帶和阻帶衰減也不能控制，所